Global landscape of protein complexes in the yeast Saccharomyces cerevisiae Export

@article{citeulike:560813, abstract = {Identification of protein–protein interactions often provides insight into protein function, and many cellular processes are performed by stable protein complexes. We used tandem affinity purification to process 4,562 different tagged proteins of the yeast Saccharomyces cerevisiae. Each preparation was analysed by both matrix-assisted laser desorption/ionization–time of flight mass spectrometry and liquid chromatography tandem mass spectrometry to increase coverage and accuracy. Machine learning was used to integrate the mass spectrometry scores and assign probabilities to the protein–protein interactions. Among 4,087 different proteins identified with high confidence by mass spectrometry from 2,357 successful purifications, our core data set (median precision of 0.69) comprises 7,123 protein–protein interactions involving 2,708 proteins. A Markov clustering algorithm organized these interactions into 547 protein complexes averaging 4.9 subunits per complex, about half of them absent from the MIPS database, as well as 429 additional interactions between pairs of complexes. The data (all of which are available online) will help future studies on individual proteins as well as functional genomics and systems biology.}, author = {Krogan, Nevan J. and Cagney, Gerard and Yu, Haiyuan and Zhong, Gouqing and Guo, Xinghua and Ignatchenko, Alexandr and Li, Joyce and Pu, Shuye and Datta, Nira and Tikuisis, Aaron P. and Punna, Thanuja and Peregr\~{A}­n-Alvarez, Jos\~{A}{\copyright} M. and Shales, Michael and Zhang, Xin and Davey, Michael and Robinson, Mark D. and Paccanaro, Alberto and Bray, James E. and Sheung, Anthony and Beattie, Bryan and Richards, Dawn P. and Canadien, Veronica and Lalev, Atanas and Mena, Frank and Wong, Peter and Starostine, Andrei and Canete, Myra M. and Vlasblom, James and Wu, Samuel and Orsi, Chris and Collins, Sean R. and Chandran, Shamanta and Haw, Robin and Rilstone, Jennifer J. and Gandi, Kiran and Thompson, Natalie J. and Musso, Gabe and St Onge, Peter and Ghanny, Shaun and Lam, Mandy H. Y. and Butland, Gareth and Altaf-Ul, Amin M. and Kanaya, Shigehiko and Shilatifard, Ali and O'Shea, Erin and Weissman, Jonathan S. and Ingles, C. James and Hughes, Timothy R. and Parkinson, John and Gerstein, Mark and Wodak, Shoshana J. and Emili, Andrew and Greenblatt, Jack F.}, citeulike-article-id = {560813}, citeulike-linkout-0 = {http://dx.doi.org/10.1038/nature04670}, citeulike-linkout-1 = {http://dx.doi.org/10.1038/nature04670}, citeulike-linkout-2 = {http://view.ncbi.nlm.nih.gov/pubmed/16554755}, citeulike-linkout-3 = {http://www.hubmed.org/display.cgi?uids=16554755}, day = {22}, doi = {10.1038/nature04670}, issn = {0028-0836}, journal = {Nature}, keywords = {interaction, protein, yeast}, month = {March}, number = {7084}, pages = {637--643}, posted-at = {2006-04-02 20:08:46}, priority = {5}, publisher = {Nature Publishing Group}, title = {Global landscape of protein complexes in the yeast Saccharomyces cerevisiae}, url = {http://dx.doi.org/10.1038/nature04670}, volume = {440}, year = {2006} }

TY - JOUR ID - citeulike:560813 L3 - citeulike-article-id:560813 N2 - Identification of protein–protein interactions often provides insight into protein function, and many cellular processes are performed by stable protein complexes. We used tandem affinity purification to process 4,562 different tagged proteins of the yeast Saccharomyces cerevisiae. Each preparation was analysed by both matrix-assisted laser desorption/ionization–time of flight mass spectrometry and liquid chromatography tandem mass spectrometry to increase coverage and accuracy. Machine learning was used to integrate the mass spectrometry scores and assign probabilities to the protein–protein interactions. Among 4,087 different proteins identified with high confidence by mass spectrometry from 2,357 successful purifications, our core data set (median precision of 0.69) comprises 7,123 protein–protein interactions involving 2,708 proteins. A Markov clustering algorithm organized these interactions into 547 protein complexes averaging 4.9 subunits per complex, about half of them absent from the MIPS database, as well as 429 additional interactions between pairs of complexes. The data (all of which are available online) will help future studies on individual proteins as well as functional genomics and systems biology. IS - 7084 JF - Nature SN - 0028-0836 EP - 643 TI - Global landscape of protein complexes in the yeast Saccharomyces cerevisiae PB - Nature Publishing Group VL - 440 SP - 637 KW - interaction KW - protein KW - yeast AU - Krogan, Nevan AU - Cagney, Gerard AU - Yu, Haiyuan AU - Zhong, Gouqing AU - Guo, Xinghua AU - Ignatchenko, Alexandr AU - Li, Joyce AU - Pu, Shuye AU - Datta, Nira AU - Tikuisis, Aaron AU - Punna, Thanuja AU - Peregrín-Alvarez, José AU - Shales, Michael AU - Zhang, Xin AU - Davey, Michael AU - Robinson, Mark AU - Paccanaro, Alberto AU - Bray, James AU - Sheung, Anthony AU - Beattie, Bryan AU - Richards, Dawn AU - Canadien, Veronica AU - Lalev, Atanas AU - Mena, Frank AU - Wong, Peter AU - Starostine, Andrei AU - Canete, Myra AU - Vlasblom, James AU - Wu, Samuel AU - Orsi, Chris AU - Collins, Sean AU - Chandran, Shamanta AU - Haw, Robin AU - Rilstone, Jennifer AU - Gandi, Kiran AU - Thompson, Natalie AU - Musso, Gabe AU - St Onge, Peter AU - Ghanny, Shaun AU - Lam, Mandy AU - Butland, Gareth AU - Altaf-Ul, Amin AU - Kanaya, Shigehiko AU - Shilatifard, Ali AU - O'Shea, Erin AU - Weissman, Jonathan AU - Ingles, James AU - Hughes, Timothy AU - Parkinson, John AU - Gerstein, Mark AU - Wodak, Shoshana AU - Emili, Andrew AU - Greenblatt, Jack PY - 2006/03/22/ UR - http://dx.doi.org/10.1038/nature04670 ER -